import os
from collections.abc import Generator

import pytest

from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
from core.model_runtime.entities.message_entities import (
    AssistantPromptMessage,
    ImagePromptMessageContent,
    PromptMessageTool,
    SystemPromptMessage,
    TextPromptMessageContent,
    UserPromptMessage,
)
from core.model_runtime.entities.model_entities import AIModelEntity, ModelType
from core.model_runtime.errors.validate import CredentialsValidateFailedError
from core.model_runtime.model_providers.stepfun.llm.llm import StepfunLargeLanguageModel


def test_validate_credentials():
    model = StepfunLargeLanguageModel()

    with pytest.raises(CredentialsValidateFailedError):
        model.validate_credentials(
            model='step-1-8k',
            credentials={
                'api_key': 'invalid_key'
            }
        )

    model.validate_credentials(
        model='step-1-8k',
        credentials={
            'api_key': os.environ.get('STEPFUN_API_KEY')
        }
    )

def test_invoke_model():
    model = StepfunLargeLanguageModel()

    response = model.invoke(
        model='step-1-8k',
        credentials={
            'api_key': os.environ.get('STEPFUN_API_KEY')
        },
        prompt_messages=[
            UserPromptMessage(
                content='Hello World!'
            )
        ],
        model_parameters={
            'temperature': 0.9,
            'top_p': 0.7
        },
        stop=['Hi'],
        stream=False,
        user="abc-123"
    )

    assert isinstance(response, LLMResult)
    assert len(response.message.content) > 0


def test_invoke_stream_model():
    model = StepfunLargeLanguageModel()

    response = model.invoke(
        model='step-1-8k',
        credentials={
            'api_key': os.environ.get('STEPFUN_API_KEY')
        },
        prompt_messages=[
            SystemPromptMessage(
                content='You are a helpful AI assistant.',
            ),
            UserPromptMessage(
                content='Hello World!'
            )
        ],
        model_parameters={
            'temperature': 0.9,
            'top_p': 0.7
        },
        stream=True,
        user="abc-123"
    )

    assert isinstance(response, Generator)

    for chunk in response:
        assert isinstance(chunk, LLMResultChunk)
        assert isinstance(chunk.delta, LLMResultChunkDelta)
        assert isinstance(chunk.delta.message, AssistantPromptMessage)
        assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True


def test_get_customizable_model_schema():
    model = StepfunLargeLanguageModel()

    schema = model.get_customizable_model_schema(
        model='step-1-8k',
        credentials={
            'api_key': os.environ.get('STEPFUN_API_KEY')
        }
    )
    assert isinstance(schema, AIModelEntity)


def test_invoke_chat_model_with_tools():
    model = StepfunLargeLanguageModel()

    result = model.invoke(
        model='step-1-8k',
        credentials={
            'api_key': os.environ.get('STEPFUN_API_KEY')
        },
        prompt_messages=[
            SystemPromptMessage(
                content='You are a helpful AI assistant.',
            ),
            UserPromptMessage(
                content="what's the weather today in Shanghai?",
            )
        ],
        model_parameters={
            'temperature': 0.9,
            'max_tokens': 100
        },
        tools=[
            PromptMessageTool(
                name='get_weather',
                description='Determine weather in my location',
                parameters={
                    "type": "object",
                    "properties": {
                      "location": {
                        "type": "string",
                        "description": "The city and state e.g. San Francisco, CA"
                      },
                      "unit": {
                        "type": "string",
                        "enum": [
                          "c",
                          "f"
                        ]
                      }
                    },
                    "required": [
                      "location"
                    ]
                  }
            ),
            PromptMessageTool(
                name='get_stock_price',
                description='Get the current stock price',
                parameters={
                    "type": "object",
                    "properties": {
                      "symbol": {
                        "type": "string",
                        "description": "The stock symbol"
                      }
                    },
                    "required": [
                      "symbol"
                    ]
                  }
            )
        ],
        stream=False,
        user="abc-123"
    )

    assert isinstance(result, LLMResult)
    assert isinstance(result.message, AssistantPromptMessage)
    assert len(result.message.tool_calls) > 0